The following information was taken from meeting notes (meetings on 6/4/2015 and 5/20/2015)
In Ag & Life Science, I suspect the computer allocation has decreased due to Moore's law (it's cheaper to get computers that can process genetic data now than it was in 2005). Engineering allocations seem to be somewhat department-related (clustering of green and blue values, in particular). The business school seems remarkably standardized - the amount decreased in 2011-2013, but otherwise has been at approximately the same level (with extremely low variance).
Lab space and lab equipment are obviously only relevant for some colleges. The proportion and raw amount of funding for lab space and equipment in LAS has decreased, while the amount of funding in engineering and human sciences has increased (though the proportion of the funding package has stayed reasonably consistent).
The recession seems to have hit graduate student support fairly hard (relative to other expenses). Looking at the gross amount of funding allocated for graduate students, we see that startup packages in engineering and human sciences include more support for graduate students than in the past (this is particularly dramatic in human sciences, though the amount of funding is still overall lower than in engineering). In the other colleges, the amount of support for graduate students has stayed relatively consistent over the past 10 years.
Summer funding seems to be fairly common in some areas (business, some of LAS) and almost unheard of in others (design, vet med).
Moving expenses amounts seem to be reasonably consistent across colleges. The business college seems to once again have a standard package that may change year to year with occasional negotiation. The same may be true of the vet med college.
Datasets from OSPA contain information on proposals and awards from 2005-2010 and 2010-2015 (4 total databases).
The following sections are intended to explore some of the limitations of the Proposal and Award datasets. They are not essential for understanding the subsequent analysis. ### Proposals
Some categories of proposals occur in FY06-FY10 but not in FY11-FY16. We do not have proposal type data for FY06-FY10. This would be useful to have, but does not seem to be present in the database.Similarly, we don't have information on the funding type for FY11-FY16. It may be useful to exclude Master Agreements, etc. from the data if no similar category exists in FY11-FY16.
Other differences between the two proposal datasets are unsurprising, such as that there are no pending proposals from FY06-FY10. Proposals are roughly evenly distributed over time, with a slight spike that corresponds to April - July 2009 (presumably, the American Recovery and Reinvestment Act proposals). Next, we consider the timeline for each proposal. Proposals have a submission date, a start date (presumably, when funding would begin), and an end date (when funding would cease).There is clearly some periodicity in the funding cycle (end dates, in particular) likely caused by differences between the academic year, government fiscal year, and calendar year.
Examining this from a slightly different perspective, we consider the difference between proposal submission dates and the start and end dates in those proposals.17% of proposals appear to start before they are submitted, and 0.28% also end before they are submitted.
Looking at the funding duration directly, we see that proposals tend to provide funding over 1-5 years, though very few do extend 10 or more years into the future. A few proposals extend 100 years into the future; this situation occurs when an amount of money is donated for some purpose and can be used at any point.The length of funding also differs between the two datasets as a result of the difference in start date calculations.
Award status differs between the two files as well; this is to be expected (more Active awards should be in the FY11-FY16 data, for instance). "Final" and "Executed" awards are present in FY11-FY16; I am currently tracking down what those statuses imply. Finally, we explore the amount of grant funding by year. Grants spanning many years are allocated to the midpoint of the funding range.Results from Google Scholar were aggregated between July 6 and July 12, 2015. Google search results (and corresponding BibTeX citations) were collected for results as follows:
| Query | Criteria/Example |
|---|---|
| Author Name | "Smith, John" |
| Date | Year>=2005 |
| Text Contains | "Iowa State University" |
Results were also filtered to ensure that the results were in areas that John Smith at Iowa State would publish in (where possible, ambiguities were resolved by referring to an online CV).
Above, the x-axis shows time at Iowa State (or rather, time since hired), and the y-axis shows the yearly publications (books, articles, etc.). The blue lines indicate departmental averages over time (loess smooth), where there is sufficient data to compute such averages. From this broad overview, we see that publications in many departments peak at approximately 5 years, and then tail off slightly by year 10.
Further analysis is provided in the Merged Data section.
We'll begin by looking at the timeline - how many years at ISU are necessary before grant applications are successful? We split this by college and faculty rank (as we'd expect that full professors who are hired should be able to command grant money sooner than new faculty). Subsequent graphs show data from hired professors (i.e. not adjuncts, affiliates, lecturers, or clinicians).
The most noticeable difference between colleges is that in engineering, assistant professors get grants about five years after they are hired, and it is very rare for professors at that stage in their careers not to get grant funding. This trend is present (though less pronounced) in Ag & Life Sciences and Human Sciences as well, though some assistant professors in those colleges seem to get funding much earlier in their careers (perhaps because of large grants given to groups of professors). In Liberal Arts and Sciences, grant funding does seem to increase with experience for some hires, but perhaps because LAS includes both arts (which are less grant-reliant) and sciences, this trend is less pronounced than in other colleges.
In order to examine the effect of startup funding on grant receipts over a career of variable duration, we will examine the distribution of startup funding by college, categorizing startup costs by the quartile (calculated for the hire's college). Below, vertical lines mark these quantiles
Using these quantile calculations, we then can examine total grants received as explained by years since hired.
It is important to note several caveats at this point: first, hires are not separated out by faculty rank or position, so hires whose primary responsibilities include administrative work may command large startup packages but bring in relatively little grant funding. Additionally, different colleges have different funding structures: LAS, for instance, may need to provide lab startup funding for science based departments, but would not have to provide this funding for new hires in English or History. Finally, the x-axis shows years since hire, which does not necessarily translate to years at ISU (faculty hired in 2005 may have left in 2011 after receiving tenure, for example).
Linear regression lines are provided here as (extremely) rough approximations; it may be useful to examine the right-most endpoint (rather than the entire line) as a prediction of total grant money received after 10 years at ISU.
With these caveats in mind,
The most noticeable difference between colleges is that in Engineering and AGLS, assistant professors submit proposals immediately. Most, but not all, Human Sciences professors also begin submitting grants almost immediately after they are hired. In Liberal Arts and Sciences, grant funding does seem to increase with experience for some hires, but perhaps because LAS includes both arts (which are less grant-reliant) and sciences, this trend is less pronounced than in other colleges and some professors (at all ranks) do not ever apply for grant funding. In the business college, it is incredibly rare for professors to apply for grants, and it is common that professors do not apply for grants in the design college.
As in the previous section, we will use quartiles to categorize startup funding by college so that we can examine total grants received as explained by years since hired.
It is important to note several caveats at this point: first, hires are not separated out by faculty rank or position, so hires whose primary responsibilities include administrative work may command large startup packages but bring in relatively little grant funding. Additionally, different colleges have different funding structures: LAS, for instance, may need to provide lab startup funding for science based departments, but would not have to provide this funding for new hires in English or History. Finally, the x-axis shows years since hire, which does not necessarily translate to years at ISU (faculty hired in 2005 may have left in 2011 after receiving tenure, for example). With these caveats in mind,
We initially consider the effect that startup packages have on the number of publications (as measured by results aggregated in Google Scholar). Publications here include journal articles, books, conference proceedings (such as IEEE) and miscellaneous other research articles.
We see that in general, yearly publications are tenuously related to startup package cost. Upward trends in Engineering and Human Sciences (and the downward trend in Design) are attributable generally to one or two outliers. In LAS, there is some increase in average yearly publications initially (perhaps because of the association between Department, Startup Costs, and publication expectations), but this flattens out fairly quickly.
In some LAS departments, like Computer Science, publication frequency does not appear to be overly impacted by career stage. In other departments, such as Chemistry, publications increase over time, and then may decrease after 5-6 years. Departments such as Music do not seem to have much publication pressure (at least not which would appear on Google Scholar). In the statistics department, most hires publish at least 2 papers per year throughout their careers, but after 3-5 years, some professors begin publishing at a much higher rate, perhaps due to increased collaboration (in fact, in the statistics department, papers with more than 6 authors are extremely uncommon until year 4-5 at ISU).
In all departments, however, it seems that differential startup funding does not impact publication frequency or trajectory.
In Ag & Life Sciences, publication trends seem to be highly department-dependent. In Animal Science (and, to a lesser degree, Agronomy), publications seem to primarily increase over time. In other departments, such as NREM and ABE, publications do not seem to increase over time, but are highly variable in any given year. In all departments, it does not appear that there is a significant relationship between startup funding and publishing trajectory.
In the business college, publications at (on average) 1.36 publications per year. As there are relatively few hires who have been at ISU for more than 5 years, it is difficult to draw any conclusions about publishing trajectories over time.
The College of Design seems to have relatively few publications per person, per year (as indexed by Google Scholar), in addition to relatively few hires between 2005-2015. This scarcity of data makes drawing any concludions difficult.
The College of Engineering seems to have a constant (or perhaps slowly increasing) publication rate for individuals (with considerable variability in any single year), across all departments. The Materials Science & Engineering department is notable as there seem to be two types of hires; those who publish in great volume, and those who do not publish more than 2-3 papers per year after 5 years at ISU.
There may be some small association between startup funding and publication trajectory within some departments, but it does not appear to be a simple relationship, and we do not have sufficient sample size within any single department to make strong conclusions.
In the College of Human Sciences, variability in yearly publications seems to outweigh any temporal or startup funding related trends in most departments.
In the College of Veterinary Medicine, publications seem to be confined to certain individuals, with most individuals publishing less than 5 papers per year that were indexed by Google Scholar. It may be (particularly in VDPAM) that individuals who are awarded larger startup packages are more likely to publish many papers each year.